Felton, Christopher L

Background: Effective pain management is crucial for both comfort and outcomes, yet predicting and managing this pain is difficult. This study aimed to analyze postoperative pain in patients undergoing hand surgery at the Mayo Clinic Florida, examining how patient characteristics and anxiety affect pain outcomes. Methods: We conducted a single-arm clinical trial at Mayo Clinic Florida, recruiting patients undergoing hand surgery. Preoperative pain and anxiety were assessed using the Pain Catastrophizing Scale (PCS) and State-Trait Anxiety Inventory (STAI). Postoperatively, patients used an iPhone app to record pain levels and medication use every four hours. Devices were collected three days after surgery. We analyzed the relationship between demographics, PCS, STAI scores, and pain levels using linear and logistic regression models. All statistical tests were two-sided with significance set at p < 0.05, analyzed with R4.2.2. Results: Data were collected from 62 patients (62.9% women, 37.1% men) undergoing hand surgery. Participants were mainly White (90.3%), with 50% being in the middle-aged adult group. Most had low anxiety levels (80.6% STAI-S, 82.3% STAI-T) and low catastrophizing (61.3% PCS). Postoperative pain was low, with median scores between 1.0 and 2.0 over three days. Demographics, anxiety, and catastrophizing were not significant predictors of pain levels. Logistic regression showed time as a significant factor, with pain levels peaking on Day 3. Conclusions: Postoperative pain after hand surgery was generally low, with time being a significant predictor of increased pain. Demographic factors, anxiety, and catastrophizing did not significantly affect pain levels. Pain management should emphasize time-sensitive interventions and ongoing monitoring.

ABSTRACT Introduction Military transport can induce whole-body vibrations, and combat almost always involves high impact between lower extremities and the ground. Therefore, robust splinting technology is necessary for lower extremity fractures in these settings. Our team compared a novel one-step spray-on foam splint (FastCast) to the current military standard structured aluminum malleable (SAM) splint. Materials and Methods Ten cadaveric specimens were subjected to complete tibia/fibula osteotomy. Specimens were fitted with custom accelerometer and gyroscope sensors superior and inferior to the fracture line. Each specimen underwent fracture and splinting from a standard of care SAM splint and an experimental FastCast spray foam splint in a randomized order. Each specimen was manually transported to an ambulance and then released from a 1 meter height to simulate impact. The custom sensors recorded accelerations and rotations throughout each event. Repeated-measures Friedman tests were used to assess differences between splint method within each event and between sensors within each splint method. Results During splinting, overall summation of change and difference of change between sensors for accelerations and rotations were greater for SAM splints than FastCast across all axes (P ≤ 0.03). During transport, the range of acceleration along the linear superior/inferior axis was greater for SAM splint than FastCast (P = 0.02), as was the range of rotation along the transverse plane (P &lt; 0.01). On impact, the summation of change observed was greater for SAM splint than FastCast with respect to acceleration and rotation on the posterior/anterior and superior/inferior axes (P ≤ 0.03), and the cumulative difference between superior and inferior sensors was greater for SAM than FastCast with respect to anterior-axis rotation (P &lt; 0.05). Conclusion FastCast maintains stabilization of fractured lower extremities during transport and impacts to a significantly greater extent than SAM splints. Therefore, FastCast can potentially reduce the risk of fracture complications following physical stressors associated with combat and extraction.

(1) Background: Telemetry units allow the continuous monitoring of vital signs and ECG of patients. Such physiological indicators work as the digital signatures and biomarkers of disease that can aid in detecting abnormalities that appear before cardiac arrests (CAs). This review aims to identify the vital sign abnormalities measured by telemetry systems that most accurately predict CAs. (2) Methods: We conducted a systematic review using PubMed, Embase, Web of Science, and MEDLINE to search studies evaluating telemetry-detected vital signs that preceded in-hospital CAs (IHCAs). (3) Results and Discussion: Out of 45 studies, 9 met the eligibility criteria. Seven studies were case series, and 2 were case controls. Four studies evaluated ECG parameters, and 5 evaluated other physiological indicators such as blood pressure, heart rate, respiratory rate, oxygen saturation, and temperature. Vital sign changes were highly frequent among participants and reached statistical significance compared to control subjects. There was no single vital sign change pattern found in all patients. ECG alarm thresholds may be adjustable to reduce alarm fatigue. Our review was limited by the significant dissimilarities of the studies on methodology and objectives. (4) Conclusions: Evidence confirms that changes in vital signs have the potential for predicting IHCAs. There is no consensus on how to best analyze these digital biomarkers. More rigorous and larger-scale prospective studies are needed to determine the predictive value of telemetry-detected vital signs for IHCAs.